Appgain
AI

AI Engineer Intern

Appgain · الجيزة, GZ, EG

Actively hiring Posted about 1 month ago

We are looking for a curious and driven AI Engineer Intern to join our engineering team. In this role, you will work at the intersection of data science and software engineering, helping us build, test, and deploy machine learning models. You will be part of a fast-paced environment where your work will directly contribute to making our products "smarter" and more efficient.

Key Responsibilities

  • Data Preparation: Assist in collecting, cleaning, and labeling datasets to ensure high-quality input for ML models.
  • Model Development: Help implement and fine-tune machine learning algorithms (e.g., NLP, Computer Vision, or Predictive Analytics) using modern frameworks.
  • Prototyping: Build "Proof of Concept" (PoC) models to test the feasibility of new AI features.
  • Testing & Evaluation: Run experiments to evaluate model performance (accuracy, precision, recall) and document the results.
  • Collaboration: Work closely with Developers and Project Manager to integrate AI models into our existing software architecture.
  • Research: Stay up-to-date with the latest AI trends and research papers to suggest innovative solutions for our business challenges.

Requirements & Technical Skills

  • Education : degree in Computer Science, Data Science, Mathematics, or a related field.
  • Programming: Strong proficiency in Python (essential) and familiarity with libraries like NumPy, Pandas, and Matplotlib.
  • AI Frameworks: Basic experience with PyTorch, TensorFlow, or Scikit-learn.
  • Problem Solving: A logical mindset and the ability to troubleshoot complex algorithmic issues.
  • Experience with LLMs (Large Language Models) and prompt engineering.
  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud).
  • Knowledge of Version Control (Git).
  • Participation in Kaggle competitions or open-source AI projects.
  • Soft Skills: Strong communication skills and the ability to explain technical concepts to non-technical stakeholders

Internship location : Giza - Pyramids Gardens

Internship Tybe : on site

Education:

  • Bachelor's (Preferred)

Experience:

  • Ai engineer: 1 year (Preferred)
  • Python: 1 year (Preferred)
  • LLMs and prompt engineering.: 1 year (Preferred)
  • Git: 1 year (Preferred)
  • AWS, Azure, or Google Cloud): 1 year (Preferred)

Location:

  • Giza (Preferred)

Work Location: In person

Tags & focus areas

Used for matching and alerts on DevFound
Internship Ai Ai Engineer Machine Learning Data Science Computer Vision
Common Questions

Frequently asked questions

Quick answers about how DevFound's AI matching, resumes, and referrals work.

DevFound's AI Copilot ingests your profile, goals, and live job data to deliver curated matches in seconds. Every match includes a resume variant, suggested referrals, and interview prep so you can act immediately. The more feedback you provide, the sharper the Copilot becomes.

AI-led job searches shrink the hours spent sifting through boards and formatting resumes. DevFound pairs automation with your personal outreach, so you reserve energy for interviews and negotiation. Traditional networking still matters, but AI gives you a lift before you even send a message.

Modern AI roles expect comfort with production-grade code, data fluency, and practical ML tooling. The strongest candidates pair deep technical chops with storytelling—translating model impact to product, GTM, and exec partners. Continuous learning keeps you ahead as stacks evolve.

DevFound rewards active seekers. Keep your profile fresh, respond to match quality prompts, and enable alerts so you never miss a role. The AI prioritizes companies and teams that align with your feedback, accelerating both introductions and interview invites.

High-density tech hubs continue to host the deepest AI talent pools, yet distributed teams are catching up fast. Use DevFound filters to hone in on onsite, hybrid, or fully remote roles and watch openings expand across time zones.

DevFound aggregates thousands of remote AI openings and flags the nuances—core hours, async culture, and visa needs—up front. The Copilot also recommends how to position your distributed work experience so hiring managers know you can thrive on a remote team.